Long-Short vs Long-Only Implementation of Equity Factors
How should be equity factor strategies implemented? In a long-only (smart beta) way? As a long-short strategy, as most of the hedge funds usually do? Or in a partially-hedged fashion by going long equity factor and shorting market to offset some of the market risks? There is no one universal answer as it depends on the investment mandate and constraints of each fund manager contemplating to implement factor investing strategies. But recent academic paper written by Benaych-Georges, Bouchaud and Ciliberti suggests that it’s a good idea to go in the direction of long-short implementation (if it’s possible). Managing short book can be challenging; however, the added benefit of lower correlation among strategies gives resultant factor portfolio a significant boost in the return-to-risk ratio (even after accounting for realistic implementation and shorting costs).
Authors: Benaych-Georges, Bouchaud, Ciliberti
Title: Equity Factors: To Short Or Not To Short, That is the Question
What is the best market-neutral implementation of classical Equity Factors? Should one use the specific predictability of the short-leg to build a zero beta Long-Short portfolio, in spite of the specific costs associated to shorting, or is it preferable to ban the shorts and hedge the long-leg with — say — an index future? We revisit this question by focusing on the relative predictability of the two legs, the issue of diversification, and various sources of costs. Our conclusion is that, using the same Factors, a Long-Short implementation leads to superior risk-adjusted returns than its Hedged Long-Only counterpart, at least when Assets Under Management are not too large.
Notable quotations from the academic research paper:
“Equity Factor investing has become increasingly popular over the past decade. There is a wide variety of ways these factors can be converted into predictive signals and realistic portfolios. The primary criterion concerns the market exposure of the portfolio: are we looking for a market-neutral implementation of these factors, with the long and short legs of the portfolio off-setting its overall beta exposure, or are we concerned with so-called smart-beta strategies, where the portfolio has a positive beta exposure to the equity market, but is tilted in the direction of said factors?
Both approaches make sense, of course, and correspond to different asset management mandates and different investor profiles. Still, for any given portfolio we can always identify and isolate the portfolio‘s exposure to the equity index and analyse the performance of its market neutral, active component.
As an example, in the smart-beta style of implementations, this market neutral component can be represented by a portfolio with long-only equity positions, hedged by a short equity index futures. This is in fact a realistic, cost-aware set-up, which allows one to build a market-neutral factor strategy
An alternative is the classical Long-Short equity portfolio, with an explicit short position on some stocks. The question that we are going to address in this paper is whether any of these two implementations yields significantly better results for the active, market-neutral risk component of the portfolio, in particular when realistic transaction costs are accounted for.
Or, stated differently: Are explicit short positions beneficial or detrimental to equity factor strategies?
More recently, the authors of [Blitz, Baltussen, van Vliet (2019), When Equity Factors Drop Their Shorts] have posted a study which suggests that an optimal implementation of market-neutral equity factors should not contain explicit short positions at all. Not only long signals seem to be of better quality than short signals, but also long positions provide a more diversified exposure to different factors than the shorts. The contribution of the present study to the debate consists in proposing a realistic, cost-aware framework allowing to compare a Long-Short equity portfolio to a beta-Hedged Long-Only one.
First, we see that the LH (long-hedged) implementation of individual factors leads to Sharpe Ratios that are comparable, on average, to those of the LS (long-short) implementation. But we now see that the LH implementations of the different factors are way more correlated than their LS counterparts.
Taking the factors’ Sharpe ratios and their correlations into account, we compute the weight of each factor in the portfolio with maximum Sharpe in both cases (LH and LS). We see, as expected, that the LS implementation is much more diversified between the different factors (see Fig. 7). Note that better diversification allows one to expect more robustness of the out-of-sample performance.
Finally, the P&Ls of the LH and LS implementations of aggregated factors (with equal weights) are presented in Fig. 8 (left). The Sharpe ratio of the LS implementation is found to be ~1, significantly higher than the one of the LH implementation ( 0.56). Let us emphasize that all costs (trading costs, leverage financing costs of LS, and borrowing costs of LS) are included in these P&L.“
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